Podcast
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Explain the components of Automatic Speech Recognition (ASR) and the challenges and issues in ASR based application development.
Explain the components of Automatic Speech Recognition (ASR) and the challenges and issues in ASR based application development.
The components of ASR include acoustic model, language model, and pronunciation model. The challenges in ASR include dealing with noisy environments, speaker variability, and continuous speech recognition. Issues in ASR based application development involve language and dialect variations, limited vocabulary, and real-time processing.
What are the components of Natural Language Processing and how do they contribute to the understanding of natural languages?
What are the components of Natural Language Processing and how do they contribute to the understanding of natural languages?
The components of Natural Language Processing include lexicography, syntax, semantics, and pragmatics. Lexicography deals with the vocabulary and word usage, syntax focuses on the structure of sentences, semantics is concerned with the meaning of words and sentences, and pragmatics addresses the practical use of language in different contexts. These components collectively contribute to the understanding of natural languages.
Discuss the concepts of formal languages and grammars, including the Chomsky hierarchy and the resolution of ambiguities.
Discuss the concepts of formal languages and grammars, including the Chomsky hierarchy and the resolution of ambiguities.
Formal languages and grammars are categorized according to the Chomsky hierarchy, which includes regular, context-free, context-sensitive, and recursively enumerable languages. Left-associative and ambiguous grammars pose challenges in language processing, requiring resolution of ambiguities. Top-down and bottom-up parsers are used to address these challenges.
Explain the role of Computation Linguistics in understanding natural languages, including morphology, Part of Speech Tagging (POS), and parsing techniques.
Explain the role of Computation Linguistics in understanding natural languages, including morphology, Part of Speech Tagging (POS), and parsing techniques.
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Which model is introduced in Module-4 for recognizing and parsing natural language structures?
Which model is introduced in Module-4 for recognizing and parsing natural language structures?
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Describe the concept of semantics and knowledge representation in the context of natural language processing, including semantic networks and logic.
Describe the concept of semantics and knowledge representation in the context of natural language processing, including semantic networks and logic.
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What is the focus of Module-3 in the context of natural language processing?
What is the focus of Module-3 in the context of natural language processing?
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Which concept is covered in Module-5 of the course?
Which concept is covered in Module-5 of the course?
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What is the main focus of Module-2?
What is the main focus of Module-2?
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What is the main topic of Module-1 in the course?
What is the main topic of Module-1 in the course?
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